Andrew J. Park

Testing perception of crime in a virtual environment

Fear of crime is a central topic in the field of victimization. In particular, criminologists are interested in the environmental structures and cues that generate fear. Research has shown that fear of crime has a direct impact on pedestrian navigation through the urban setting. Most studies have used traditional methods such as surveys or interviews. Researchers have debated the methodological issues stemming from these methods. This article introduces two explorative studies which use a virtual environment (VE) as a research tool for the study of fear of crime. The benefits associated to using VEs in this field of research are discussed. The development, implementation and results of these two studies are presented. The limitations and future directions of VE experiments are discussed.

Dynalink: A Framework for Dynamic Criminal Network Visualization

Understanding the temporal development and patterns of criminal networks is important for law enforcement and intelligence agencies to investigate and prevent crimes. Extracting and visualizing criminal networks from a large amount of crime data has been a challenge over the past years. In particular, the visualization of the dynamic development of such networks over time has been difficult in many ways. Recent advancement of visual analytics provides new analytical reasoning tools to explore and analyze a large amount of data with interactive visual interfaces. By employing the ideas of visual analytics, we propose here a framework to visualize dynamic criminal networks, which is called Dynalink. The interactive and visual features of Dynalink can be useful in discovering and analyzing both relational and temporal patterns of criminal networks.

Testing Elderly People's Fear of Crime Using a Virtual Environment

The fear of crime refers to the fear of being a victim of potential crimes. This fear often restricts normal daily activities and lowers the quality of life. For elderly people, fear of crime has a practical effect on their activities. Thus, the study of the fear of crime has been one of the important subjects in the victimization study. However, since there was no common agreement on the definition of the fear of crime among researchers, the methodological issues of measuring the fear of crime have been debated for decades. The methods that are most frequently used in measuring fear of rime are victimization surveys and interviews. These methods have inherent limitations of measuring fear of crime particularly with elderly people. This paper explores a new way of measuring fear of crime using a virtual environment from the behavioural aspects. The case study shows the research experiments with the elderly people who make a choice of routes in the virtual environment that replicates the Vancouver Chinatown. The experimental results suggest that this new method of measuring fear of crime using a virtual environment has many benefits particularly when it is used with elderly people. The limitations of this method and the future research are discussed.

An agent-based model and computational framework for counter-terrorism and public safety based on swarm intelligencea

AbstractPublic safety has been a great concern in recent years as terrorism occurs everywhere. When a public event is held in an urban environment like Olympic games or soccer games, it is important to keep the public safe and at the same time, to have a specific plan to control and rescue the public in the case of a terrorist attack. In order to better position public safety in communities against potential threats, it is of utmost importance to identify existing gaps, define priorities and focus on developing approaches to address those.In this paper, we present a system which aims at providing a decision support, threats response planning and risk assessment. Threats can be in the form of Chemical, Biological, Radiological, Nuclear and Explosive (CBRNE) weapons and technologies. In order to assess and manage possible risks of such attacks, we have developed a computational framework of simulating terrorist attacks, crowd behaviors, and police or safety guards’ rescue missions. The characteristics of crowd behaviors are modeled based on social science research findings and our own virtual environment experiments with real human participants. Based on gender and age, a person has a different behavioral characteristic. Our framework is based on swarm intelligence and agent-based modeling, which allows us to create a large number of people with specific behavioral characteristics. Different test scenarios can be created by importing or creating 3D urban environments and putting certain terrorist attacks (such as bombs or toxic gas) on specific locations and time-lines.

Identifying high risk crime areas using topology

Computational criminology is an area of research that joins advanced theories in criminology with theories and methods in mathematics, computing science, geography and behavioural psychology. It is a multidisciplinary approach that takes the strengths of several disciplines and, with semantic challenges, builds new methods for the analysis of crime and crime patterns. This paper presents a developing algorithm for linking the geographic and cognitive psychology sides of criminology research with a prototype topology algorithm that joins local urban areas together using rules that define similarity between adjacent small units of analysis. The approach produces irregular shapes when mapped in a Euclidean space, but which follow expectations in a non-Euclidean topological sense. There are high local concentrations or hot spots of crime but frequently there is a sharp break on one side of the hot spot and with a gradual diffusion on the other. These shapes follow the cognitive psychological way of moving from one location to another without noticing gradual changes or conversely being aware of sharp changes from one location to the next. This article presents a pattern modeling approach that uses topology to spatially identify the concentrations of crime and their crisp breaks and gradual blending into adjacent areas using the basic components: interior, boundary and exterior. This topology algorithm is used to analyze crimes in a moderate sized city in British Columbia.

A Proposal of Undergraduate Curriculum to Include Research Under the Experiential Learning Framework

The primary objective of this paper is to argue the importance of undergraduate research, and it provides a theoretical foundation in employing undergraduate research as part of the experiential learning approach. Recently experiential learning has become a popular learning strategy in university education. Research in university is mainly performed by graduate students and faculty. Occasionally advanced undergraduate students take a chance to participate in research. This paper, however, argues that the majority of undergraduate students will benefit from and should be involved in undergraduate research. If we view undergraduate research as part of the experiential learning strategy, then the rationale for involving undergraduate students in research becomes apparent.

The Virtual Environment in Communication of Age-Friendly Design

There is a mismatch between the design of many communities and the needs of older persons. Many communities are designed for people who are at work during the day and at home during the night. Their main travel method is by car. Typically the connectivity and walkability between housing and services, such as doctor’s offices and grocery stores, have not been a priority. However, with the increasing number of older persons aging-in-place, many communities are in the process of major transformation of their environments to be more supportive and age friendly. To date, over 100 local communities across Canada are engaged in Age-Friendly Communities (AFC) activities and five provinces have identified AFC as a priority (PHAC, 2010).

Temporal analysis of radical dark web forum users

Extremist groups have turned to the Internet and social media sites as a means of sharing information amongst one another. This research study analyzes forum posts and finds people who show radical tendencies through the use of natural language processing and sentiment analysis. The forum data being used are from six Islamic forums on the Dark Web which are made available for security research. This research project uses a POS tagger to isolate keywords and nouns that can be utilized with the sentiment analysis program. Then the sentiment analysis program determines the polarity of the post. The post is scored as either positive or negative. These scores are then divided into monthly radical scores for each user. Once these time clusters are mapped, the change in opinions of the users over time may be interpreted as rising or falling levels of radicalism. Each user is then compared on a timeline to other radical users and events to determine possible connections or relationships. The ability to analyze a forum for an overall change in attitude can be an indicator of unrest and possible radical actions or terrorism.

A Decision Support System for Crowd Control Using Agent-Based Modeling and Simulation

Crowd control has been one of the important responsibilities for law enforcement officers. Whether a crowdis formed for political reasons or sporting events, they can turn to be violent, disrupting public peace/order and damaging properties in a public place. Effective and efficient crowd control tactics can keep the safety of both the innocent public and the crowd who are involved with (violent) collective behaviours. In order to devise and test such tactics, a decision support system called SimCrowd Control has been developed using the technique of agent-based modeling and simulation (ABMS). The system employs a realistic crowd model developed based on social science research studies. At the early stage of the SimCrowd Control system, simple crowd control tactics were tested against the crowd model by simulating the Vancouver Stanley Cup Riot which happened in 2011. The limitations of the current system and future plans are discussed.

Detecting Key Players in Criminal Networks Using Dynalink

Detecting key players in criminal networks is an important aspect of criminal investigation because it promotes the efficient use of available resources (human, financial, time, etc.). In this paper, we propose a new technique of detecting key players in co-offending networks using the Dynalink framework. Dynalink is a social network visualization tool developed intentionally employs visual analytics to visualize networks interactively over time. This novel technique proposed here employs the intuitive concept of centrality in detecting key players in criminal networks. The tool will allow crime analysts and investigators to visualize networks interactively over time and use this technique to discover criminal patterns and key players.